Four graded components, every page has the full rubric.
Assignments
Each assignment is a professional deliverable with a real audience: a case analysis a practitioner could act on, a short video someone outside this class could watch, a consultant memo an organization could decide from, and a running inventory of real problems you have seen firsthand.
| Component | Weight | Who | Due |
|---|---|---|---|
| Ethics Case Analysis | 25% | Individual | Week 7 |
| Digital Storytelling Project | 25% | Individual or pair | Week 12, screened Week 13 |
| Technology Strategy Pitch | 25% | Pairs | Capacity brief Week 11, briefing Week 13, memo finals week |
| Participation | 25% | Individual | All semester |
Rubric-by-rubric notes on what separates strong work from adequate work on each of these are on the marks that move a grade page.
Ethics Case Analysis. You dismantle one deployed technology and attribute its harm or its success to a specific human decision. You pick the case (a harm case or a success case) and who the write-up is addressed to (no one, one colleague, or a board), then record a 5-minute walkthrough a non-technical stakeholder could follow. Launches Week 3, due Week 7.
Digital Storytelling Project. A 3-to-5-minute video on one of three tracks: your own story of how you came to this work, an explainer that moves one named audience to take one specific action on a problem you have seen firsthand, or a piece a real organization could use. Awareness is not the deliverable: the brief you write commits you to a segment, a behavioral ask, an efficacy claim, and a distribution channel. Before you script, you collect strong examples in your chosen form and submit what you learned from them. Standing and positionality, consent, accessibility, and honest representation are graded; the class screens the finished pieces in Week 13. The video is separate from the pitch and shares nothing with it but your calendar.
Technology Strategy Pitch. Pairs take one interview with one organization about a technology decision it faces, run a capacity assessment on it, and write the memo a consultant would leave behind, then brief it to the class in Week 13. Recommending against adoption, argued well, scores full marks.
Participation. Three pieces: attendance and discussion (8%), a Problem Inventory of real service problems logged across the semester (10%), and the weekly question board (7%). Posts to the class Design Walls are bonus.
Weekly checkpoints
Every major deliverable is introduced early and checkpointed in class before it is due. Bold rows are graded submissions; the rest are working checkpoints with class time attached.
| Week | Ethics Case (25%) | Digital Story (25%) | Strategy Pitch (25%) | Participation |
|---|---|---|---|---|
| 4 | Template released | |||
| 5 | Pick your case | Track chosen | Problem Inventory, two entries in | |
| 6 | Launched; lab is the supervised rehearsal | Organization named | ||
| 7 | Due at start of class | |||
| 8 | Subject locked; ABT sentence approved on Tracks B and C | Funder grant teardown run in lab | Problem Inventory check, two entries expected, feedback only | |
| 9 | Ginsberg footage requested, Track C | Launched; capacity assessment run and interview protocol red-teamed in lab | ||
| 10 | Video notes shared; communication brief or story of self sheet drafted in the story circle; storyboard started | The interview, any time through Week 11 | ||
| 11 | Rough cut (homework before class); captions corrected and peer bug-bounty in lab; right-of-reply viewing scheduled | Capacity brief due | ||
| 12 | Due, with corrected caption file, transcript, and source log | Plan outline and evaluation metrics due; the four pre-pitch pressure-tests are put to the room, and the decision you would redesign goes into the accessibility and ethics sections | ||
| 13 | Screened to the class | Briefing in class; feedback packet collected. Memo due via Canvas during finals week |
AI policy
You may use AI on every assignment, and two steps are required every time: disclose what tool you used and for what, and verify every claim an AI tool returns against a primary source before it enters your work. A confident, wrong, unchecked “fact” costs more points than not using AI at all.
You help write this course policy. In Week 5 the class co-drafts and signs the AI Disclosure Charter, which becomes the disclosure form attached to every submission.
Do not enter partner or client information into AI tools. Remove or alter identifying details first, and if you cannot de-identify a transcript or case detail, omit it. The NASW Code of Ethics already requires you to keep client information confidential (Week 7).
The reasons behind the rule are on the week pages: fabricated output in Week 4, the energy and water cost in Week 12, and the firms that build these tools in Week 8.